DBMS > Blueflood vs. Lovefield vs. TimesTen vs. Tkrzw vs. Yaacomo

System Properties Comparison Blueflood vs. Lovefield vs. TimesTen vs. Tkrzw vs. Yaacomo

Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

Scalable TimeSeries DBMS based on Cassandra

Embeddable relational database for web apps written in pure JavaScript

An in-memory SQL relational database that delivers microsecond response and high throughput for OLTP applications. TimesTen can be deployed as a standalone database or as a cache to a backend Oracle database.

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.06
Rank	#354	Overall
	#35	Time Series DBMS

Score	0.23
Rank	#299	Overall
	#135	Relational DBMS

Score	1.23
Rank	#163	Overall
	#74	Relational DBMS

Score	0.00
Rank	#386	Overall
	#61	Key-value stores

Website

blueflood.io

google.github.io/lovefield

www.oracle.com/database/technologies/related/timesten.html

dbmx.net/tkrzw

yaacomo.com

Technical documentation

github.com/rax-maas/blueflood/wiki

github.com/google/lovefield/blob/master/docs/spec_index.md

docs.oracle.com/en/database/other-databases/timesten/index.html

Developer

Rackspace

Google

Oracle

originally founded in HP Labs it was acquired by Oracle in 2005

Mikio Hirabayashi

Q2WEB GmbH

Initial release

2013

2014

1998

2020

2009

Current release

2.1.12, February 2017

Release 22.1

0.9.3, August 2020

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache 2.0

commercial

Open Source

Apache Version 2.0

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

JavaScript

C++

Server operating systems

Linux
OS X

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

IBM AIX Power PC 64-bit
Linux arm64
Linux x86-64
Solaris SPARC 64
Solaris SPARC/x86
Solaris x86-64

Linux
macOS

Android
Linux
Windows

Data scheme

predefined scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

yes

APIs and other access methods

HTTP REST

ODBC
ODP.NET
Oracle Call Interface (OCI)
Pro*C/C++ programming interfaces
SQL and PL/SQL via JDBC

JDBC
ODBC

Supported programming languages

JavaScript

C
C++
Java
Node.js
PL/SQL
Python

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

PL/SQL

Triggers

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

none

Multi-source replication
Source-replica replication

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

by means of logfiles and checkpoints

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using MemoryDB

yes

using specific database classes

yes

User concepts

Access control

fine grained access rights according to SQL-standard

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